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JACIII Vol.21 No.3 pp. 507-517
doi: 10.20965/jaciii.2017.p0507
(2017)

Paper:

Generalized Predictive PID Control for Main Steam Temperature Based on Improved PSO Algorithm

Zhongda Tian, Shujiang Li, and Yanhong Wang

College of Information Science and Engineering, Shenyang University of Technology
Shenyang 110870, China

Received:
October 29, 2016
Accepted:
January 16, 2017
Online released:
May 19, 2017
Published:
May 20, 2017
Keywords:
main steam temperature, generalized predictive control, predictive PID, improved particle swarm optimization
Abstract

The large inertia and long delay characteristics of main steam temperature control system in thermal power plants will reduce the system control performance. In order to improve the system control performance, a generalized predictive PID control for main steam temperature strategy based on improved particle swarm optimization algorithm is proposed. The performance index of incremental PID controller of main control loop and PD controller of auxiliary control loop based on generalized predictive control algorithm is established. An improved particle swarm optimization algorithm with better fitness and faster convergence speed is proposed for online parameters optimization of performance index. The optimal control value of PID controller and PD controller can be obtained. The simulation experiment compared with fuzzy PID and fuzzy neural network is carried out. Simulation results show that proposed control method has faster response speed, smaller overshoot and control error, better tracking performance, and reduces the lag effect of the control system.

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Last updated on Jul. 25, 2017